Machine Learning Ops Engineer, Sr. Associate

Key Skills

Aartificial intelligence, Apache Hadoop, AWS, Continuous Integration & Continuous Delivery - CI/CD, Data science techniques, Design, DevOps, DevSecOps, Docker, Git, IT, Jenkins, Kubernetes-K8s, Linux Operating system, Machine learning techniques, MLOps tools, Python Programming, PyTorch, RStudio, Shell Scripting language, TensorFlow, Terraform

Job Description

The Center for Data Science and Artificial Intelligence (CDSAi) is the innovative corporate Analytics group within New York Life. We are a rapidly growing entrepreneurial department which aims to design, create, and offer innovative data-driven solutions for many parts of the enterprise. We are aided by New York Life’s existing business with a large market share in individual life insurance. We have the freedom to explore external data sources and new statistical techniques and are excited about delivering a whole new generation of predictive analytics and artificial intelligence solutions.

In fact, we are building one of the first multivariate model-based continuous risk differentiations in the industry. We are also working on models for differentiated advertising allocation by geography, channel, and segment. Geographic analytics on agents and customers, application fraud detection, agent success prediction and client prospecting analytics (off-line and on-line) are other exciting examples of enormous incremental value from analytics. Our products are implemented into real-time core business processes and decisions that drive the company (e.g., underwriting, pricing, agent recruiting, prospecting, advertising allocation, new product development).

We work with data ranging from demographics, credit, and geo data to detailed medical data (medical test results, diagnosis, prescriptions) and social media information. We have a modern computing environment with a solid suite of data science/modeling tools and packages, and a large (but manageable) group of well-trained professionals at various levels to support you. Life insurance is on the verge of huge change. This is a chance to drive the transformation of an industry.

The Center for Data Science and Artificial Intelligence (CDSAi) is the 60-person innovative corporate Data Science group within New York Life, led by Chief Analytics Officer Glenn Hofmann (https://www.linkedin.com/in/glennhofmann/). We are a rapidly growing entrepreneurial department which designs, creates, and deploys innovative data-driven solutions for many parts of the enterprise. For more opportunities in data science, please visit our website (https://www.newyorklife.com/careers/corporate/data-science)

You will support and expand an industry leading Kubernetes-based MLOps platform. You will work with analytics and ML engineers to enable data and ML pipelines to best-practice standards. You will help productionize and support ML solutions in the cloud. Most importantly, you will be an instrumental member of a highly technical MLOps team lead by Boris Simanovich (https://www.linkedin.com/in/boris-simanovich/)

Responsibilities

1. Maintain the CDSAi MLOps Kubernetes infrastructure using Terraform
2. Support Data Scientists/ML Engineers and Data Engineers in implementing efficient, secure, and scalable CI/CD pipelines
3. Enforce Git standards
4. Implement architectural patterns for on-prem and cloud data/ML pipelines and solutions
5. Build strong relationships and partner with technology (IT) stakeholders to enable systems integrations, deployments, etc.
6. Function as a platform expert and help contribute to solution design and implementation decisions
7. Work independently with minimal supervision and be part of a collaborative team
8. Work with Project Managers and Scrum Masters to execute stories and provide milestones
9. Effectively articulate information and ideas to a diverse group of people
10. Stay up to date with the latest MLOps trends/emerging technologies and look for opportunities to improve the stack

Required qualifications

• 5+ years of industry experience
• Hands-on coding skills in Terraform, Python and Linux/Shell scripting
• Experience with containers (Docker) and container orchestration (Kubernetes)
• Solid understanding of CI/CD and DevOps/DevSecOps best practices
• Experience working with data teams and automating ML and other data/compute-intensive applications
• Excellent command of Git (branching strategies, security, Jenkins integration, pull request process, etc.)
• Experience with cloud compute environments (AWS) along with cloud-native tools
• Understanding of real-time and batch inference
• Have an agile mindset
• Degree in computer science, engineering, or relevant work experience

Preferred: 

• Understanding of ML frameworks (sklearn, TensorFlow, PyTorch, etc.)
• Experience working with big data platforms (Redshift, Snowflake, Hadoop, etc.)
• Architecture, design patterns, production scaling/optimization
• Exposure to Geospatial (GIS) platforms
• Exposure to RStudio
• Insurance industry experience